GPU-ACCELERATED IMAGE RETEXTURING IN GRADIENT DOMAIN

Ping Li, Hanqiu Sun, Jianbing Shen

2010

Abstract

This paper presents the novel GPU-accelated image retexturing approach for both high and low dynamic range images using our newly invented fast NLM filtering. Integrating the fast Maclaurin polynomial kernel filter and the latest GPU-CUDA acceleration, our approach is able to produce real-time high quality retexturing for objects of the interest, while preserving the original shading and similar texture distortion. We apply our revised NLM filtering to the initial depth map to ensure smoothed depth field for retexturing. Our approach using GPU-based fast NLM filtering is designed in parallel, and easy to develop on latest GPUs. Our testing results have shown the efficiency and satisfactory performance using our approach.

References

  1. Buades, A. and Coll, B. and Morel, J. (2006). A review of image denoising algorithms, with a new one, Multiscale Modeling and Simulation, 4(2), 490-530.
  2. Chatterjee, P. and Milanfar, P. (2008). A generalization of non-local means via kernel regression. Proc. of IS&T Conf. on Computational Imaging VI, San Jose.
  3. Choudhury, P. and Tumblin, J. (2003). The trilateral filter for high contrast images and meshes. Eurographics Symposium on Rendering 7803, 186-196.
  4. Fang, H. and Hart, J. (2006). Rototexture: automated tools for texturing raw video. IEEE Trans. on Visualization and Computer Graphics, 12(6), 1580-1589.
  5. Fang, H. and Hart, J. (2004). Textureshop: texture synthesis as a photograph editing tool. International Conference on Computer Graphics and Interactive Techniques, ACM New York, 354-359.
  6. Gonzalez, R. and Woods, R. (2008). Digital image processing (3rd ed.). NJ: Pearson/Prentice-Hall.
  7. Guo, Y. and Wang, J. and Zeng, X. and Xie, Z. and Sun, H. and Peng, Q. (2005). Image and video retexturing. Computer Animation and Virtual Worlds, 16, 451-461.
  8. Guo, Y. and Sun, H. and Peng, Q. and Jiang, Z. (2008). Mesh-Guided Optimized Retexturing for Image and Video. IEEE Transactions on Visualization and Computer Graphics, 14(2), 426-439.
  9. Hoefflinger, B. (2007). High-dynamic-range (HDR) vision. Berlin: Springer.
  10. Horn, B. and Brooks, M. (1989). Shape from shading. Mass: MIT press Cambridge.
  11. Jäjne, B. (2005). Digital image processing, concepts algorithms, & scientific app.. Berlin: Springer-Verlag.
  12. Kazhdan, M. and Hoppe, H. (2008). Streaming Multigrid for Gradient-Domain Operations on Large Images. Proceedings of ACM SIGGRAPH 2008, 27(3).
  13. Khan, E. and Reinhard, E. and Fleming, R. and Bulthoff, H. (2006). Image-based material editing. Proceedings of ACM SIGGRAPH 2006, 25(3), 654-663.
  14. Levin, A. and Rav-Acha, A. and Lischinski, D. (2008). Spectral matting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(10), 1699-1712.
  15. Li, Y. and Sun, J. and Tang, C. and Shum, H. (2004). Lazy snapping. ACM Trans. Graph, 23(3), 303-308.
  16. Lindenbaum, M. and Fischer, M. and Bruckstein, A. (1994). On Gabor's contribution to image enhancement. Pattern Recognition, 27(1), 1-8.
  17. Liu, Y. and Lin, W. and Hays, J. (2004). Near-regular texture analysis and manipulation. Proceedings of ACM SIGGRAPH 2004, ACM New York, 368-376.
  18. McCann, J. and Pollard, N. (2008). Real-Time GradientDomain Painting. Proceedings of ACM SIGGRAPH 2008, 27(3).
  19. Oh, B. and Chen, M. and Dorsey, J. and Durand, F. (2001). Image-based modeling and photo editing. Proceedings of ACM SIGGRAPH 2001, ACM New York, 433-442.
  20. Perez, P. and Gangnet, M. and Blake, A. (2003). Poisson image editing, ACM Trans. Graphics, 22(3), 313-318.
  21. Perona, P. and Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7), 629-639.
  22. Shen, J. and Jin X. and Sun H. (2007). High dynamic range image tonemapping and retexturing using fast trilateral filtering. The Visual Computer, 23(9), 641- 650.
  23. Smith, S. and Brady, J. (1997). SUSAN - A new approach to low level image processing. International Journal of Computer Vision, 23(1), 45-78.
  24. Tsin, Y. and Liu, Y. and Ramesh, V. (2001). Texture replacement in real images. Proc. IEEE CVPR 2001, 2, IEEE Computer Society.
  25. Yaroslavsky, L. (1985). Digital picture processing. Berlin: Springer-Verlag and New York: Springer-Verlag.
Download


Paper Citation


in Harvard Style

Li P., Sun H. and Shen J. (2010). GPU-ACCELERATED IMAGE RETEXTURING IN GRADIENT DOMAIN . In Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010) ISBN 978-989-674-027-6, pages 29-34. DOI: 10.5220/0002827400290034


in Bibtex Style

@conference{imagapp10,
author={Ping Li and Hanqiu Sun and Jianbing Shen},
title={GPU-ACCELERATED IMAGE RETEXTURING IN GRADIENT DOMAIN},
booktitle={Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010)},
year={2010},
pages={29-34},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002827400290034},
isbn={978-989-674-027-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010)
TI - GPU-ACCELERATED IMAGE RETEXTURING IN GRADIENT DOMAIN
SN - 978-989-674-027-6
AU - Li P.
AU - Sun H.
AU - Shen J.
PY - 2010
SP - 29
EP - 34
DO - 10.5220/0002827400290034